Abstract : To design high performance, practically implementable control laws, it is important to have the appropriate tools for design and analysis. These tools should enable the following: (1) they should be based on robustness theory that is nonconversative with respect to the type of uncertainty being considered; (2) they should allow performance to be measured in a meaning full way; (3) they should yield controllers that are of sufficiently low order to be implemented on control processors with limited throughout capabilities; (4) they should be implemented via efficient numerical algorithms. The research cited in this final report has led to the further development of robustness theories and algorithms which include phase information regarding the uncertainty. In addition, this research has expanded the theory of optimal and suboptimal reduced-order control design and led to the development of new continuation algorithms for H2 optimal reduced-order modeling and control based on the optimal projection equations. Finally, a new fixed-structure approach to complex structured singular value controller synthesis has been developed. The approach a priori constrains the order of the D-scales in the optimization process and can lead to much more robust controllers than standard D-K iteration and curve fitting approaches.